AC/pandas.ipynb

161 lines
4.8 KiB
Plaintext
Raw Permalink Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "42a5aacc-5e39-4262-99dc-f4fc3a2c58a4",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Имя</th>\n",
" <th>Возраст</th>\n",
" <th>Баллы</th>\n",
" <th>Категория</th>\n",
" <th>Прогноз_балла</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Анна</td>\n",
" <td>21</td>\n",
" <td>89</td>\n",
" <td>A</td>\n",
" <td>106.8</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Борис</td>\n",
" <td>22</td>\n",
" <td>76</td>\n",
" <td>B</td>\n",
" <td>91.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Виктор</td>\n",
" <td>23</td>\n",
" <td>95</td>\n",
" <td>A</td>\n",
" <td>114.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Галина</td>\n",
" <td>24</td>\n",
" <td>82</td>\n",
" <td>B</td>\n",
" <td>98.4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Дмитрий</td>\n",
" <td>21</td>\n",
" <td>91</td>\n",
" <td>A</td>\n",
" <td>109.2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Елена</td>\n",
" <td>25</td>\n",
" <td>88</td>\n",
" <td>C</td>\n",
" <td>105.6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Имя Возраст Баллы Категория Прогноз_балла\n",
"0 Анна 21 89 A 106.8\n",
"1 Борис 22 76 B 91.2\n",
"2 Виктор 23 95 A 114.0\n",
"3 Галина 24 82 B 98.4\n",
"4 Дмитрий 21 91 A 109.2\n",
"5 Елена 25 88 C 105.6"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"\n",
"# Создаем расширенный DataFrame (с добавлением категории)\n",
"data = {\n",
" \"Имя\": [\"Анна\", \"Борис\", \"Виктор\", \"Галина\", \"Дмитрий\", \"Елена\"],\n",
" \"Возраст\": [21, 22, 23, 24, 21, 25],\n",
" \"Баллы\": [89, 76, 95, 82, 91, 88],\n",
" \"Категория\": [\"A\", \"B\", \"A\", \"B\", \"A\", \"C\"]\n",
"}\n",
"df = pd.DataFrame(data)\n",
"\n",
"# 1. Добавляем новый столбец с коэффициентом 1.2 (отличие от примера)\n",
"df[\"Прогноз_балла\"] = df[\"Баллы\"] * 1.2\n",
"\n",
"# 2. Группировка данных по категории\n",
"grouped = df.groupby(\"Категория\").agg({\"Баллы\": [\"mean\", \"max\"]})\n",
"\n",
"# 3. Фильтрация\n",
"filtered_df = df[df[\"Баллы\"] > 85]\n",
"\n",
"# Вывод результата в последней строке\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "5d0af1f0-3cd7-4720-b1e3-361b88b300d6",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}